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Presents feature wavelet packets (FWP) a new method of chatter feature extraction in milling process based on wavelet packets transform (WPT) and using vibration signal. Studies the procedure of automatic feature selection for a given process. Establishes an exponential autoregressive (EAR) model to extract limit cycle behavior of chatter since chatter is a nonlinear oscillation with limit cycle. And gives a way to determine FWT’s number, and experimental data to assess the effectiveness of the WPT feature extraction by unforced response of EAR model of reconstructed signal.
Presents feature wavelet packets (FWP) a new method of chatter feature extraction in milling process based on wavelet packet transform (WPT) and using vibration signal. Studies of the procedure of automatic feature selection for a given process. To extract limit cycle behavior of chatter since chatter is a nonlinear oscillation with limit cycle. And gives a way to determine FWT’s number, and experimental data to assess the effectiveness of the WPT feature extraction by unforced response of EAR model of reconstructed signal.